Merge branch 'master' into master

CONTRIBUTING.md

@@ -6,9 +6,7 @@ This guide shows how to make contributions to [tensorflow.org](https://www.tenso
 
 See the
 [TensorFlow docs contributor guide](https://www.tensorflow.org/community/contribute/docs)
-for guidance. For questions, the
-[[email protected]](https://groups.google.com/a/tensorflow.org/forum/#!forum/docs)
-mailing list is available.
+for guidance. For questions, check out [TensorFlow Forum](https://discuss.tensorflow.org/).
 
 Questions about TensorFlow usage are better addressed on
 [Stack Overflow](https://stackoverflow.com/questions/tagged/tensorflow) or the

README.md

@@ -16,7 +16,7 @@ To file a docs issue, use the issue tracker in the
 [tensorflow/tensorflow](https://github.com/tensorflow/tensorflow/issues/new?template=20-documentation-issue.md) repo.
 
 And join the TensorFlow documentation contributors on the
-[[email protected] mailing list](https://groups.google.com/a/tensorflow.org/forum/#!forum/docs).
+[TensorFlow Forum](https://discuss.tensorflow.org/).
 
 ## Community translations
 

site/en/community/contribute/docs.md

@@ -32,7 +32,7 @@ To participate in the TensorFlow docs community:
 
 For details, use the [TensorFlow API docs contributor guide](docs_ref.md). This
 shows you how to find the
-[source file](https://www.tensorflow.org/code/tensorflow/python/)
+[source file](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/)
 and edit the symbol's
 <a href="https://www.python.org/dev/peps/pep-0257/" class="external">docstring</a>.
 Many API reference pages on tensorflow.org include a link to the source file
@@ -53,9 +53,9 @@ main
 <a href="https://github.com/tensorflow/tensorflow" class="external">tensorflow/tensorflow</a>
 repo. The reference documentation is generated from code comments
 and docstrings in the source code for
-<a href="https://www.tensorflow.org/code/tensorflow/python/" class="external">Python</a>,
-<a href="https://www.tensorflow.org/code/tensorflow/cc/" class="external">C++</a>, and
-<a href="https://www.tensorflow.org/code/tensorflow/java/" class="external">Java</a>.
+<a href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/" class="external">Python</a>,
+<a href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/cc/" class="external">C++</a>, and
+<a href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/java/" class="external">Java</a>.
 
 Previous versions of the TensorFlow documentation are available as
 [rX.x branches](https://github.com/tensorflow/docs/branches) in the TensorFlow

site/en/community/contribute/docs_ref.md

@@ -8,7 +8,7 @@ TensorFlow uses [DocTest](https://docs.python.org/3/library/doctest.html) to
 test code snippets in Python docstrings. The snippet must be executable Python
 code. To enable testing, prepend the line with `>>>` (three left-angle
 brackets). For example, here's a excerpt from the `tf.concat` function in the
-[array_ops.py](https://www.tensorflow.org/code/tensorflow/python/ops/array_ops.py)
+[array_ops.py](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/array_ops.py)
 source file:
 
 ```
@@ -178,7 +178,7 @@ There are two ways to test the code in the docstring locally:
 
 *   If you are only changing the docstring of a class/function/method, then you
     can test it by passing that file's path to
-    [tf_doctest.py](https://www.tensorflow.org/code/tensorflow/tools/docs/tf_doctest.py).
+    [tf_doctest.py](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/docs/tf_doctest.py).
     For example:
 
     <pre class="prettyprint lang-bsh">

site/en/community/contribute/docs_style.md

@@ -63,7 +63,7 @@ repository like this:
 * <code>\[Basics\]\(../../guide/basics.ipynb\)</code> produces
 [Basics](../../guide/basics.ipynb).
 
-This is the prefered approach because this way the links on
+This is the preferred approach because this way the links on
 [tensorflow.org](https://www.tensorflow.org),
 [GitHub](https://github.com/tensorflow/docs){:.external} and
 [Colab](https://github.com/tensorflow/docs/tree/master/site/en/guide/bazics.ipynb){:.external}

site/en/guide/create_op.md

@@ -152,17 +152,17 @@ REGISTER_KERNEL_BUILDER(Name("ZeroOut").Device(DEVICE_CPU), ZeroOutOp);
 >   Important: Instances of your OpKernel may be accessed concurrently.
 >   Your `Compute` method must be thread-safe. Guard any access to class
 >   members with a mutex. Or better yet, don't share state via class members!
->   Consider using a [`ResourceMgr`](https://www.tensorflow.org/code/tensorflow/core/framework/resource_mgr.h)
+>   Consider using a [`ResourceMgr`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/resource_mgr.h)
 >   to keep track of op state.
 
 ### Multi-threaded CPU kernels
 
 To write a multi-threaded CPU kernel, the Shard function in
-[`work_sharder.h`](https://www.tensorflow.org/code/tensorflow/core/util/work_sharder.h)
+[`work_sharder.h`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/util/work_sharder.h)
 can be used. This function shards a computation function across the
 threads configured to be used for intra-op threading (see
 intra_op_parallelism_threads in
-[`config.proto`](https://www.tensorflow.org/code/tensorflow/core/protobuf/config.proto)).
+[`config.proto`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/protobuf/config.proto)).
 
 ### GPU kernels
 
@@ -519,13 +519,13 @@ This asserts that the input is a vector, and returns having set the
 
 *   The `context`, which can either be an `OpKernelContext` or
     `OpKernelConstruction` pointer (see
-    [`tensorflow/core/framework/op_kernel.h`](https://www.tensorflow.org/code/tensorflow/core/framework/op_kernel.h)),
+    [`tensorflow/core/framework/op_kernel.h`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op_kernel.h)),
     for its `SetStatus()` method.
 *   The condition.  For example, there are functions for validating the shape
     of a tensor in
-    [`tensorflow/core/framework/tensor_shape.h`](https://www.tensorflow.org/code/tensorflow/core/framework/tensor_shape.h)
+    [`tensorflow/core/framework/tensor_shape.h`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor_shape.h)
 *   The error itself, which is represented by a `Status` object, see
-    [`tensorflow/core/platform/status.h`](https://www.tensorflow.org/code/tensorflow/core/platform/status.h). A
+    [`tensorflow/core/platform/status.h`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/platform/status.h). A
     `Status` has both a type (frequently `InvalidArgument`, but see the list of
     types) and a message.  Functions for constructing an error may be found in
     [`tensorflow/core/platform/errors.h`][validation-macros].
@@ -668,7 +668,7 @@ There are shortcuts for common type constraints:
 
 The specific lists of types allowed by these are defined by the functions (like
 `NumberTypes()`) in
-[`tensorflow/core/framework/types.h`](https://www.tensorflow.org/code/tensorflow/core/framework/types.h).
+[`tensorflow/core/framework/types.h`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/types.h).
 In this example the attr `t` must be one of the numeric types:
 
 ```c++
@@ -1226,7 +1226,7 @@ There are several ways to preserve backwards-compatibility.
     type into a list of varying types).
 
 The full list of safe and unsafe changes can be found in
-[`tensorflow/core/framework/op_compatibility_test.cc`](https://www.tensorflow.org/code/tensorflow/core/framework/op_compatibility_test.cc).
+[`tensorflow/core/framework/op_compatibility_test.cc`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op_compatibility_test.cc).
 If you cannot make your change to an operation backwards compatible, then create
 a new operation with a new name with the new semantics.
 
@@ -1243,16 +1243,16 @@ made when TensorFlow changes major versions, and must conform to the
 You can implement different OpKernels and register one for CPU and another for
 GPU, just like you can [register kernels for different types](#polymorphism).
 There are several examples of kernels with GPU support in
-[`tensorflow/core/kernels/`](https://www.tensorflow.org/code/tensorflow/core/kernels/).
+[`tensorflow/core/kernels/`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/).
 Notice some kernels have a CPU version in a `.cc` file, a GPU version in a file
 ending in `_gpu.cu.cc`, and some code shared in common in a `.h` file.
 
 For example, the `tf.pad` has
 everything but the GPU kernel in [`tensorflow/core/kernels/pad_op.cc`][pad_op].
 The GPU kernel is in
-[`tensorflow/core/kernels/pad_op_gpu.cu.cc`](https://www.tensorflow.org/code/tensorflow/core/kernels/pad_op_gpu.cu.cc),
+[`tensorflow/core/kernels/pad_op_gpu.cu.cc`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/pad_op_gpu.cu.cc),
 and the shared code is a templated class defined in
-[`tensorflow/core/kernels/pad_op.h`](https://www.tensorflow.org/code/tensorflow/core/kernels/pad_op.h).
+[`tensorflow/core/kernels/pad_op.h`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/pad_op.h).
 We organize the code this way for two reasons: it allows you to share common
 code among the CPU and GPU implementations, and it puts the GPU implementation
 into a separate file so that it can be compiled only by the GPU compiler.
@@ -1273,16 +1273,16 @@ kept on the CPU, add a `HostMemory()` call to the kernel registration, e.g.:
 #### Compiling the kernel for the GPU device
 
 Look at
-[cuda_op_kernel.cu.cc](https://www.tensorflow.org/code/tensorflow/examples/adding_an_op/cuda_op_kernel.cu.cc)
+[cuda_op_kernel.cu.cc](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/adding_an_op/cuda_op_kernel.cu.cc)
 for an example that uses a CUDA kernel to implement an op. The
 `tf_custom_op_library` accepts a `gpu_srcs` argument in which the list of source
 files containing the CUDA kernels (`*.cu.cc` files) can be specified. For use
 with a binary installation of TensorFlow, the CUDA kernels have to be compiled
 with NVIDIA's `nvcc` compiler. Here is the sequence of commands you can use to
 compile the
-[cuda_op_kernel.cu.cc](https://www.tensorflow.org/code/tensorflow/examples/adding_an_op/cuda_op_kernel.cu.cc)
+[cuda_op_kernel.cu.cc](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/adding_an_op/cuda_op_kernel.cu.cc)
 and
-[cuda_op_kernel.cc](https://www.tensorflow.org/code/tensorflow/examples/adding_an_op/cuda_op_kernel.cc)
+[cuda_op_kernel.cc](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/adding_an_op/cuda_op_kernel.cc)
 into a single dynamically loadable library:
 
 ```bash
@@ -1412,7 +1412,7 @@ be set to the first input's shape. If the output is selected by its index as in
 
 There are a number of common shape functions
 that apply to many ops, such as `shape_inference::UnchangedShape` which can be
-found in [common_shape_fns.h](https://www.tensorflow.org/code/tensorflow/core/framework/common_shape_fns.h) and used as follows:
+found in [common_shape_fns.h](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/common_shape_fns.h) and used as follows:
 
 ```c++
 REGISTER_OP("ZeroOut")
@@ -1459,7 +1459,7 @@ provides access to the attributes of the op).
 
 Since shape inference is an optional feature, and the shapes of tensors may vary
 dynamically, shape functions must be robust to incomplete shape information for
-any of the inputs. The `Merge` method in [`InferenceContext`](https://www.tensorflow.org/code/tensorflow/core/framework/shape_inference.h)
+any of the inputs. The `Merge` method in [`InferenceContext`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/shape_inference.h)
 allows the caller to assert that two shapes are the same, even if either
 or both of them do not have complete information. Shape functions are defined
 for all of the core TensorFlow ops and provide many different usage examples.
@@ -1484,7 +1484,7 @@ If you have a complicated shape function, you should consider adding a test for
 validating that various input shape combinations produce the expected output
 shape combinations.  You can see examples of how to write these tests in some
 our
-[core ops tests](https://www.tensorflow.org/code/tensorflow/core/ops/array_ops_test.cc).
+[core ops tests](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/array_ops_test.cc).
 (The syntax of `INFER_OK` and `INFER_ERROR` are a little cryptic, but try to be
 compact in representing input and output shape specifications in tests.  For
 now, see the surrounding comments in those tests to get a sense of the shape
@@ -1497,20 +1497,20 @@ To build a `pip` package for your op, see the
 guide shows how to build custom ops from the TensorFlow pip package instead
 of building TensorFlow from source.
 
-[core-array_ops]:https://www.tensorflow.org/code/tensorflow/core/ops/array_ops.cc
-[python-user_ops]:https://www.tensorflow.org/code/tensorflow/python/user_ops/user_ops.py
-[tf-kernels]:https://www.tensorflow.org/code/tensorflow/core/kernels/
-[user_ops]:https://www.tensorflow.org/code/tensorflow/core/user_ops/
-[pad_op]:https://www.tensorflow.org/code/tensorflow/core/kernels/pad_op.cc
-[standard_ops-py]:https://www.tensorflow.org/code/tensorflow/python/ops/standard_ops.py
-[standard_ops-cc]:https://www.tensorflow.org/code/tensorflow/cc/ops/standard_ops.h
-[python-BUILD]:https://www.tensorflow.org/code/tensorflow/python/BUILD
-[validation-macros]:https://www.tensorflow.org/code/tensorflow/core/platform/errors.h
-[op_def_builder]:https://www.tensorflow.org/code/tensorflow/core/framework/op_def_builder.h
-[register_types]:https://www.tensorflow.org/code/tensorflow/core/framework/register_types.h
-[FinalizeAttr]:https://www.tensorflow.org/code/tensorflow/core/framework/op_def_builder.cc
-[DataTypeString]:https://www.tensorflow.org/code/tensorflow/core/framework/types.cc
-[python-BUILD]:https://www.tensorflow.org/code/tensorflow/python/BUILD
-[types-proto]:https://www.tensorflow.org/code/tensorflow/core/framework/types.proto
-[TensorShapeProto]:https://www.tensorflow.org/code/tensorflow/core/framework/tensor_shape.proto
-[TensorProto]:https://www.tensorflow.org/code/tensorflow/core/framework/tensor.proto
+[core-array_ops]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/array_ops.cc
+[python-user_ops]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/user_ops/user_ops.py
+[tf-kernels]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/
+[user_ops]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/user_ops/
+[pad_op]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/pad_op.cc
+[standard_ops-py]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/standard_ops.py
+[standard_ops-cc]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/cc/ops/standard_ops.h
+[python-BUILD]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/BUILD
+[validation-macros]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/platform/errors.h
+[op_def_builder]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op_def_builder.h
+[register_types]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/register_types.h
+[FinalizeAttr]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op_def_builder.cc
+[DataTypeString]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/types.cc
+[python-BUILD]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/BUILD
+[types-proto]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/types.proto
+[TensorShapeProto]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor_shape.proto
+[TensorProto]:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor.proto

site/en/guide/data.ipynb

@@ -1385,7 +1385,7 @@
         "The simplest form of batching stacks `n` consecutive elements of a dataset into\n",
         "a single element. The `Dataset.batch()` transformation does exactly this, with\n",
         "the same constraints as the `tf.stack()` operator, applied to each component\n",
-        "of the elements: i.e. for each component *i*, all elements must have a tensor\n",
+        "of the elements: i.e., for each component *i*, all elements must have a tensor\n",
         "of the exact same shape."
       ]
     },

site/en/guide/dtensor_overview.ipynb

@@ -281,7 +281,7 @@
         "id": "Eyp_qOSyvieo"
       },
       "source": [
-        "<img src=\"https://www.tensorflow.org/images/dtensor/dtensor_layout_rank2.png\" alt=\"A tensorr with it's first axis sharded across mesh dimension 'y' and it's second axis sharded across mesh dimension 'x'\" class=\"no-filter\">\n"
+        "<img src=\"https://www.tensorflow.org/images/dtensor/dtensor_layout_rank2.png\" alt=\"A tensorr with its first axis sharded across mesh dimension 'y' and it's second axis sharded across mesh dimension 'x'\" class=\"no-filter\">\n"
       ]
     },
     {
@@ -303,7 +303,7 @@
       "source": [
         "For the same `mesh_2d`, the layout `Layout([\"x\", dtensor.UNSHARDED], mesh_2d)` is a layout for a rank-2 `Tensor` that is replicated across `\"y\"`, and whose first axis is sharded on mesh dimension `x`.\n",
         "\n",
-        "<img src=\"https://www.tensorflow.org/images/dtensor/dtensor_layout_hybrid.png\" alt=\"A tensor replicated across mesh-dimension y, with it's first axis sharded across mesh dimension 'x'\" class=\"no-filter\">\n"
+        "<img src=\"https://www.tensorflow.org/images/dtensor/dtensor_layout_hybrid.png\" alt=\"A tensor replicated across mesh-dimension y, with its first axis sharded across mesh dimension 'x'\" class=\"no-filter\">\n"
       ]
     },
     {

site/en/guide/estimator.ipynb

@@ -68,7 +68,7 @@
         "id": "rILQuAiiRlI7"
       },
       "source": [
-        "> Warning: Estimators are not recommended for new code.  Estimators run `v1.Session`-style code which is more difficult to write correctly, and can behave unexpectedly, especially when combined with TF 2 code. Estimators do fall under our [compatibility guarantees](https://tensorflow.org/guide/versions), but will receive no fixes other than security vulnerabilities. See the [migration guide](https://tensorflow.org/guide/migrate) for details."
+        "> Warning: TensorFlow 2.15 included the final release of the `tf-estimator` package. Estimators will not be available in TensorFlow 2.16 or after. See the [migration guide](https://www.tensorflow.org/guide/migrate/migrating_estimator) for more information about how to convert off of Estimators."
       ]
     },
     {

site/en/guide/migrate/evaluator.ipynb

@@ -122,7 +122,7 @@
         "\n",
         "In TensorFlow 1, you can configure a `tf.estimator` to evaluate the estimator using `tf.estimator.train_and_evaluate`.\n",
         "\n",
-        "In this example, start by defining the `tf.estimator.Estimator` and speciyfing training and evaluation specifications:"
+        "In this example, start by defining the `tf.estimator.Estimator` and specifying training and evaluation specifications:"
       ]
     },
     {